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Record W2929350712 · doi:10.5539/apr.v11n3p1

Femtosecond Laser Structuring of Materials: A Review

2019· review· en· W2929350712 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueApplied Physics Research · 2019
Typereview
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsFemtosecondSiliconLaserMaterials scienceStructuringMaterials processingAbsorption (acoustics)OptoelectronicsOpticsNanotechnologyPhysicsComposite materialProcess engineering

Abstract

fetched live from OpenAlex

In this review the interaction between femtosecond laser and matter with emphasis on silicon and some metals have been appraised. For silicon, spikes are produced as a result of interaction in the presence of background gas such as SF6, or H2S with an appropriate background pressure, but spikes are not formed in the presence N2 or air. The formation of the spikes increase the infrared light absorption of silicon to near unity. Interaction of femtosecond laser with metals form periodic surface structures that make the metals exhibit many different morphological characteristics. This processing technique allows the creation of a variety of colors on a metal that ultimately lead to control of its optical properties from UV to terahertz. From the assessment made, the potential of femtosecond laser structuring of materials for cost-effective nano-manufacturing is high.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.163
GPT teacher head0.415
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it